#2006-010
Foreign Direct Investment and Technology Spillovers: Evidence from
The Indian Manufacturing Sector
Subash Sasidharan
Working Paper Series
United Nations University - Maastricht Economic and social Research and training centre on Innovation and Technology Keizer Karelplein 19, 6211 TC Maastricht, The Netherlands
Foreign Direct Investment and Technology Spillovers:
Evidence from the Indian Manufacturing Sector
Subash Sasidharan1
Abstract
During the recent period, we observe that many countries compete with each other to attract foreign investment. When MNCs invest in a host country, it is assumed that a part of their technology spills to the host country firms. But the empirical studies on spillover effects of FDI have failed to find robust empirical results about the possibility of positive spillover effects. This study is an attempt to empirically examine the spillover effects from the entry of foreign firms using firm level data of Indian manufacturing industries for the period 1994-2002. We consider both the horizontal and vertical spillover effects of FDI. Consistent with the findings of the previous studies, we find no evidence of significant horizontal spillover effects. In contrast, we find negative vertical spillover effects, although it is not statistically significant.
Keywords: Foreign Direct Investment, Horizontal Spillover, Vertical Spillover, Panel Data
JEL Code: F2, O1, O3
UNU-MERIT Working Papers
ISSN 1871-9872
Maastricht Economic and social Research and training centre on Innovation and Technology, UNU-MERIT
UNU-MERIT Working Papers intend to disseminate preliminary results of the research carried out at the institute to attract comments
1 Research Scholar (Economics), Indian Institute of Technology Bombay, India. e-mail:
subashs@iitb.ac.in
Acknowledgement: This paper was drafted during my PhD internship at UNU-INTECH Maastricht. I
have immensely benefited from the discussions and comments from Dr. Kaushalesh Lal, Anabel Marin, Dr. Ionara Costa, Geoffrey Gachino, Ngoc Pham Quang and Abraham Garcia. I also wish to thank Dr. C. Veeramani, Dr. Vinish Kathuria, Asha Sundaram, Priit Vahter, Unmesh Patnaik, Rijo M. John and Prashanth Mahagaonkar for the useful suggestions. Financial support from the UNU-INTECH is greatly appreciated.
Introduction
Since 1980s foreign direct investment (FDI)† has been a dominant form of technology transfer from developed countries to developing countries. It is based on the fact that multinational enterprises and its affiliates are an important source of international capital and technology. Foreign direct investment bring with it equipment, technical know how, management marketing and other skills (Lall 1997). It is presumed that domestic firms benefit from the externalities associated with the foreign investment through productivity improvement, exports and international integration (Costa and de Queiroz 2002). Therefore, many countries offer various kinds of incentives like tax holidays, subsidies and low tax rates to attract foreign investors.
However, the results of the studies on the positive externalities by FDI are largely inconclusive. The lack of significant horizontal spillover (within industry) effects of FDI has made the researchers to look at the possibility of vertical spillover effects. The main objective of the present study is to empirically examine the horizontal and vertical spillover effects of FDI in the Indian manufacturing sector. The study of India is of particular interest due to the surge in the foreign direct investment inflows witnessed since the onset of large scale economic restructuring in the 90s.
This paper is organised as follows. Section 2 provides an overview of the Foreign Direct Invest regime in India. The theoretical framework and empirical evidence from previous studies are presented in Section 3. Section 4 discusses the data source and methodology. Section 5 presents the empirical results. Finally, Section 6 concludes the study.
2. Foreign Direct Investment Regime in India
The process of transition from a closed to an open economy in the Indian case was a very gradual phenomenon. This is true in the case of the FDI policies also. Kumar (1994) classifies the FDI policy in India into four distinct phases. Phase one (1948-1967) was characterised by gradual liberalisation. This period is marked by a cautious approach concerning the foreign capital. Even though the policy makers were aware of importance
6
of foreign capital, it was felt that foreign capital need to be regulated in order to safeguard national interests. However, until 1956, there was no regulation on foreign capital. The industrial policy resolution passed in 1956 emphasised reservation of certain industries to the public sector. The foreign exchange crisis in 1958-59 made the government to rethink its stand on foreign capital. The government tried to offer concessions in the form of tax incentives to foreign investors. The outcome was, many MNCs started showing interest in investing in India.
Restrictive Phase (1968-79) is marked by the regulation of foreign capital and streamlining of procedures in the approval of foreign collaborations. During this period, a Foreign Investment Promotion board was set up to monitor approval of foreign collaborations exceeding 40 percent of equity. Three new enactments passed during this phase clearly underline the apathy of the policy makers to the foreign capital. The Monopolies and Trade Restrictive Act (MRTP) of 1969 required the scrutiny of the all projects involving large firms’ capacity expansion. The Indian Patents Act of 1970 was an attempt to remove the monopolistic advantages enjoyed by the multinational corporations. The act was enacted with the intention of avoiding the crowding out of domestic firms. The Foreign Exchange Regulation Act (FERA) (see Kumar 1994 for details) of 1973 required the dilution of all foreign equity to 40 percent. As a result, those multinational companies, which refused to comply with the new regulation, left the market (for example Cocoa Cola and IBM).
Third Phase (1980-1990), witnessed easing of regulation on the foreign capital. The industrial policy resolution of 1980 and 1982 announced certain liberal policy rules like delicensing of selected industries and exemption of foreign equity restriction on fully export-oriented units. Along with the adoption of liberal trade policies, government also took certain measure to allow the import of capital goods and technology. A significant consequence of the policy regime during this period is the shift in the sectoral composition of FDI from plantations, minerals and petroleum to manufacturing sector. The manufacturing sector accounted for the 85 percent of total stock of FDI by the end of 80s (Balasubramanyam and Mahambre 2003).
7
During the early nineties, India faced severe foreign exchange and balance of payments crisis. The policy makers realised that the solution is to adopt a liberal policy regime. The New Industrial Policy (NIP) resolution passed in 1991 abolished industrial licensing. NIP provides for automatic approval of FDI up to 51% of equity in a list of 34 specified high-priority, capital intensive, hi-technology industries. The prime motive of the policy makers in the adoption of the NIP has been to attract foreign direct investment in various sectors.
Table 1. FDI Inflows to India Year FDI Inflows‡ (Millions of Dollars) 1990 237 1991 75 1992 252 1993 532 1994 974 1995 2151 1996 2525 1997 3619 1998 2633 1999 2168 2000 2319 2001 3403 2002 3449 2003 4269 2004 5335 Source: World Investment Report (various issues)
Due to the liberalisation policies adopted by the Indian government since the beginning of the 90s, the foreign direct investment flows have increased steadily from 237 million dollars in 1992 to 5335 million dollars in 2004 (see Table 1). The growing presence of
‡
Notes: FDI inflows comprise capital provided (either directly or through other related enterprises) by a
foreign direct investor to a FDI enterprise, or capital received by a foreign direct investor from a FDI enterprise. FDI includes the three following components: equity capital, reinvested earnings and intra-company loans.
8
foreign firms may be attributed to the liberalization, deregulation and macroeconomic stabilization policies adopted by the Indian government. Therefore, the role of foreign investment in the form of technology transfer has come to the center stage in India’s industrial development. It has been claimed that the foreign subsidiaries poses a challenge to the domestic firms through its superior technology and other firm specific advantages. At the same time domestic firms can benefit from the externalities. The domestic Indian firms will have to develop technological capability in order to compete as well as co-operate with the foreign firms. Hence, it is important to empirically examine whether the entry of foreign firms is beneficial or detrimental to the domestic Indian firms.
3. Theoretical Framework
The empirical studies on spillover effects of FDI are based on the notion that MNCs possess superior organisational and production techniques compared to the domestic firms (Hymer 1976). MNCs can transfer technology through various means like licensing, trade, FDI, subcontracting, franchising and strategic alliances. Nevertheless, the preferred mode of technology transfer is through foreign direct investment since it can internalise the transfer of superior technological assets at little or no extra cost (Caves 1996). In addition, FDI is considered as the best means to keep control over the technological knowledge. Since the technology has the characteristic of a public good, a part of the technology spills from the MNC subsidiaries to the domestic firms. The spillovers can be in the form of improvement in the productivity of the domestic firms. This is neo-classical view on spillover effects§. The spillover effects from the FDI can be broadly classified as horizontal (sectoral) and vertical (inter-sectoral) spillover. The commonly identified channels of spillover from MNCs are illustrated in the figure below. We examine both horizontal and vertical spillovers in detail below.
§ This is in line with the “externalities” being “spillovers”, according to neo-classical theory, an externality
9 Horizontal Spillovers
The entry of foreign firms may lead to an increase in the productivity of the domestic firms in the same industry through various means. First, demonstration effects refer to the copying or the imitation of foreign firms’ technology and organisational practices by the domestic firms. Second, labour turnover arises from the mobility of the skilled and trained workers from MNCs to domestic firms. These workers are carriers of MNC’s technology. Multinationals can prevent the flow of labour by paying higher wages. On the other hand, there is a possibility of reverse labour turnover. The employees of domestic firms can move to foreign firms. Third, competition effects refers to a situation in which entry of foreign firm forces the domestic firms to increase their efficiency by improving the existing methods of production or adopt new ones. For example, MNCs usually enter markets, which are highly concentrated. The main characteristic feature of such markets is the high entry barrier created by few domestic firms. In such a scenario, the entry of foreign firm forces the domestic firms to become more efficient thereby a reduction in the market concentration. At the same time, competition from foreign firms can lead to crowding out of domestic firms. Those firms, which are unable to compete with the foreign firms, are forced to make an exit. Aitken and Harrison (1999) attribute such an effect as “market stealing effect”. In the most widely cited study about Venezuelan firms, Aitken and Harrison show that foreign firms actually divert demand from the domestic firms. Therefore in the short run, the productivity of the domestic firms decline. From the point of view of the customer, competition effects are certainly beneficial due to availability of the improved quality of products. Competition is considered as a driver of innovation also. The argument about positive competition effects hold only if domestic firms are not far below the technological frontier. On the other hand, in an industry characterised by weak firms, the entry of foreign firms may eventually lead to an exit of the weak domestic firms.
10 Vertical (Inter-Industry) Spillovers
The phenomenon of spillovers is not just confined within industries. It can arise as a result of interaction across industries. The inter industry spillover arises mainly by the customer-supplier relationship between foreign firms and domestic firms. According to Dunning (1993, p.456), “the presence of FDI has helped to raise the productivity of many domestic suppliers, and this has often had beneficial spillover effects on the rest of their operations”. It is believed that spillovers are more likely in the case of inter-industry than with in the same industry. The reason behind such a belief is that, MNCs can prevent the leakage of technology to its competitors, while it has no incentive to prevent the technology diffusion to its suppliers and clients (Javorick 2004).
Vertical spillover mechanism operates both at the upstream and downstream sector. MNCs usually source their raw materials and components from domestic suppliers. The incentive for the MNC to source from the domestic market arises in the case of high transportation costs between the home and host country as well certain regulations imposed by the host country government like local content requirements. The MNCs usually assists the local suppliers to achieve technical and organisational competence by providing technological assistance as well as training programmes for employees of local supplier firms (Lall 1978). MNCs follow stringent quality requirements regarding their inputs supplied by local firms. As a result, the domestic supplier firms improve their quality of products and patterns of production process. The entry of foreign firms may increase the demand for intermediate inputs by local firms. Therefore through backward linkage mechanism, productivity of domestic firms may improve.
On the other hand, if the MNCs prefer to source from their international supplier, the domestic firms will have to upgrade in order to meet the global and follow sourcing **. Those supplying firms failing to meet the requirements of the MNCs or unable to meet the import competition will be forced to exit from the market. As a result a negative vertical spillover can arise in such an eventuality. Markusen and Venables (1999) in a
11
theoretical model show that as a result of the contact with the multinational firms, local input suppliers can emerge strong in the long run make the MNCs to leave the market.
Figure1: Channels of Technology Transfer and Spillover from Foreign Direct Investment
Licensing
MNE
Trade FDI Strategic
Alliances Franchising Subcontracting Host Country Subsidiary Vertical Spillover Horizontal Spillover
The occurance of vertical spillover is based on certain set of conditions. The foremost factor is the extent of the vertical integration between foreign firms and its domestic suppliers. MNCs focussing on the domestic market have the incentive to source from the domestic suppliers. While, an export oriented MNC subsidiary might prefer the international supplier of the parent company in order to meet the international quality standards in the export markets. This is true in the case where MNCs are unable to find the domestic supplier meeting its stringent quality requirements. Based on the above discussion, we can conclude that the net effects of horizontal and vertical spillover can be either positive or negative.
Large number of studies has appeared in the recent years on the impact of FDI on host country firm productivity growth through spillovers††. The studies pertain to developed, developing and transition economies using both cross sectional and panel data. The pioneering studies (Caves 1974; Globerman 1979; Blomstrom and Persson 1986) using cross-sectional data mostly found evidence of positive effects. However, these studies were criticised for the reason that they were unable to take into consideration the industry and time effects. The evidence of positive spillover from foreign subsidiaries may be due to the possibility that MNCs tend to invest in high productivity industries. The availability of panel data has enabled the researchers to rectify the shortcomings of using cross-sectional data. Studies undertaken with the panel data reveal negative or insignificant effects (Aitken and Harrison 1999, Djankov and Hoekman 2000; Konings 2001). Some of the studies based on panel data show positive effect, but depending on certain factors like the absorptive capacity (Kinoshita 2001; Girma 2005) and the extent of the technology gap between domestic and foreign firms (Kokko 1994; Castellani and Zanfei 2003). Panel data also enables the researchers to take into account the time lag involved in the absorption of spillovers by domestic firms. In an extensive review of studies on spillover effects of FDI, Gorg and Strobl (2001) conclude that “the results of productivity spillover studies do not seem to be affected by whether the studies use sector
†† See Blomstrom and Kokko (1998) and Gorg and Greenaway (2004) for an extensive survey ofthe
14 or firm level data, but that it is important whether the data used are cross-sectional or panel data”.
The lack of positive spillover effects within industries using panel data has made researchers to search for the possibility of FDI spillover across industries. These studies are based on the belief that domestic firms in downstream and upstream sectors may be benefiting from the linkage with the foreign firms. Vertical spillover variables are constructed using input-output tables. Some of the recent studies focussing on inter-industry spillovers have found positive effects through backward and forward linkages with the foreign subsidiaries (Schoors and van der Tol (2002) for Hungary; Javorick (2004) for Lithuania; Blalock (2002) for Indonesia). However, some other studies on the linkage effects illustrate mixed results. For example, Yudeva et al (2003) study on Russian manufacturing firms find negative forward and backward linkage effects. Similarly, Merlevede and Schoors (2005) focus on the inter-sectoral effects of spillovers in Romanian firms. They find evidence of positive forward spillovers but backward spillover is found only in the case of export-oriented sectors.
Table 2. Studies on Intra-Industry and Inter-Industry Spillovers of FDI
Authors Data Year Level of
Aggregation
Country HS F B Blomstrom and
Persson (1983) c.s 1970/1975 ind Mexico + Blomstrom and
Wolf (1986) c.s 1970/1975 ind Mexico +
Kokko (1994) c.s 1970 ind Mexico +
Blomstrom and Sjoholm (1999)
c.s 1991 micro Indonesia +
Sjoholm (1999) c.s 1980/1991 micro Indonesia + Aitken and
Harrison (1999) panel 1976-89 micro Venezuela - Haddad and
Harrison (1993) panel 1985-89 micro Morocco ? Djankov and
Hoekman (2000) panel 1993-96 micro Czech Rep. - Konings (2001) panel 1993-97 1994-97 1993-97 micro Bulgaria, Poland, Romania - ? Zukowska and
Gagelmann (2000) panel 1993-97 Micro Poland - Kugler (2001) panel 1974-98 ind Colombia ?
15 2002) 1990-97
Siddharthan and Lal
(2004) panel 1993-2000 micro India +
Narula and Marin (2005)
panel 1992-2001
micro Argentina ?
Yudeva et al.
(2003) panel 1993-97 micro Russia + - -
Blalock and Gertler
(2004) panel 1988-96 micro Indonesia ? +
Javorick (2004) panel 1996-2000 micro Lithuania ? -/? + Javorick and Spatareanu (2004) panel 1998-2000 micro Romania - + +/- Schoors and van
der Tol (2002) c.s 1997/1998 micro Hungary + + - Merlevede and
Schoors (2005) panel 1996-2001 micro Romania - + -/+ Blyde et al. panel
1995-2000 micro Venezuela - - +/?
c.s.: cross sectional data ind: industry
Micro include both plant and firm level data HS: Horizontal spillover
F: Forward Linkages B: Backward Linkages ?: insignificant effects
Table 2 provides a summary of the selected studies carried out on productivity spillovers based on cross-sectional or panel data from developing and transition economies‡‡. It is clear from the table that cross-sectional studies report positive horizontal spillover effects while majority of the panel data studies report either negative or insignificant spillovers. Therefore, from the results of the previous studies, we can safely conclude that evidence on positive spillovers is weak.
3. Data Source and Methodology
The data for our study is obtained from the PROWESS database provided by the Center for Monitoring Indian Economy (CMIE). We also use the input-output table for the year 1998-99 provided by the Central Statistical Organisation (2005). The PROWESS database contains information of about 9800 firms registered with the Bombay Stock Exchange. For our study, we have drawn data for the manufacturing sector firms (Sector 15-36 in the NIC classification), resulting in a sample of 4900 manufacturing firms. The
16
data covers the period from 1994-2002. Firms are categorized according to the NIC 1998 code. PROWESS database provided information on foreign equity, value of output, sales, exports, imports, wages, materials costs and fixed assets.
Table. 3 Classification of Firms by Industry in the Year 2002 NIC
Code Industry Classification DomesticFirms Firms FDI* Firms All 2/3*100
15 Food Products and Beverages 280 26 306 8.5
16 Tobacco Products 3 3 6 50.0
17 Textiles 305 14 319 4.4
18 Wearing Apparel 43 2 45 4.4
19 Leather and Leather Products 22 1 23 4.3
20 Wood and of Products of Wood
and Cork, Except Furniture; 14 0 14 0.0
21 Paper and Paper Products 74 8 82 9.8
22 Publishing, Printing and Reproduction of Recorded
Media 18 1 19 5.3
23 Coke, Refined Petroleum
Products and Nuclear Fuel 30 4 34 11.8
24 Chemicals and Chemical,
Products 541 63 604 10.4
25 Rubber and Plastic Products 153 18 171 10.5
26 Other Non-Metallic Mineral
Products 97 14 111 12.6
27 Basic Metals 256 16 272 5.9
28 Fabricated Metal Products 70 7 77 9.1
29 Machinery and equipment 139 40 179 22.3
30 Office machinery and
Computing Machinery 19 2 21 9.5
31 Electrical Machinery and
Apparatus 92 12 104 11.5
32 Radio, Television and
Communication Equipment 62 11 73 15.1
33 Medical, Precision and Optical Instruments, Watches and
Clocks 35 7 42 16.7
34 Motor Vehicles 96 26 122 21.3
35 Other Transport Equipment 31 3 34 8.8
36 Furniture; Manufacturing
N.E.C. 36 2 38 5.3
Total 2416 280 2696 10.4
Based on Authors Calculations from the PROWESS database *FDI firms are those firms with foreign equity of 10 percent or more
17
For the purpose of our study, we have used an unbalanced panel data. The use of an unbalanced panel selection can be justified on the grounds that very few firms exit from the data set. Those firms, which report zero value added, and those firms, which re-enter the database after a gap, are excluded for analysis. The final sample varies 2696 and 2720 firms. The sectoral composition of the firms is given in the Table 3 above. From table 3 we can see that during the year 2002, 10% of the firms have foreign ownership. The foreign presence is highest in the Tobacco industry followed by machinery and equipment, non-metallic mineral products. It can be observed that in the wood and wood products industry has no foreign owned firm.
For the present study all those firms having foreign equity greater that 10%§§ of the total equity are classified as foreign firms. In addition to the variable representing the ownership, we also construct two spillover indicators i.e., horizontal and vertical. The horizontal spillover indicator captures the spillover effects from the multinational in the same industry. Vertical spillover indicator captures the effect of foreign subsidiary from the industries to which it supplies. The details of the input variables (Capital, Labour and Materials) construction used in the production function estimation are explained in detail in Appendix I. We explain in detail below about the construction of horizontal and vertical spillover indicators.
Horizontal Spillover: Previous studies have used different measures to proxy spillovers. Most of the studies use either the share of employment or output of the foreign firm. Following Blalock (2002) and Kathuria (2002), we can represent it as: share of foreign firms output to total industry output.
Vertical Spillover: Vertical Spillover variable is used as measure to capture productivity spillovers to those domestic firms, which supply inputs to multinationals. The indicator has been constructed as follows.
j j i ij j horizontal Vertical
∑
≠ = α18
We proxy the share of a firm’s output sold to foreign firm by the share of an industry output sold to foreign firms in different downstream industries. We can construct this variable using an input-output table. Input-Output table provides details about the amount supplied by an industry to downstream industries. We use an input output table for the year 1998-99 provided by the Central Statistical Organisation (2005) for the same. From the firm level data we can obtain the share of foreign firms output in each industry. Where αij is the proportion of output of sector i supplied to sector j from the 1998-99 input output matrix***. We exclude the inputs sold within the sector since this effect is captured by the horizontal spillover variable.
3.1 Performance of Domestic and Foreign Firms
In this section we make a comparison between foreign and domestic performance based on certain key variables like exports, technology imports and R&D (Table 4).
Table. 4 Comparison of Domestic and Foreign Firms
Domestic Firms (%) Foreign Firms (%)
1994 2002 1994 2002 R&D Intensity 0.2 0.5 0.3 0.7 Export Intensity 8.4 13.2 10.1 13.8 Technology Imports Intensity 3 1.3 4.4 2.2
*Based on Author’s own calculations from PROWESS Database
R&D Intensity is the share of R&D Expenditure to the total sales. Export Intensity is the share of total exports to the total sales. Technology Imports is the share of the capital goods imports plus the remittances on royalties and licence fees to the total sales.
R&D Intensity: It can be observed from the table that the expenditure on R&D is found to be very negligible in the Indian manufacturing sector. It is not even one percent of the total sales. During the period 1994-2002, it can be seen that there has been a marginal increase in the R&D spending by both the domestic and foreign oriented firms. From the data we can observe that foreign firms are more R&D intensive than the local firms.
*** The details of the construction of the input-output coefficient and concordance table are given in
19 Export Intensity:It is normally assumed that the foreign firms are more export intensive compared to the domestic firms. But, it is indeed a surprise to find from our data that the domestic firms are as export intensive as the foreign firms.Even though the foreign firms had an edge in the initial years, we can clearly observe a trend of domestic firms catching up with the foreign firms. We find that the export intensity of both the domestic and foreign firms is almost the same in the year 2002. The possible explanation might be the depreciation of the rupee during the nineties and the liberalisation policy adopted in the nineties might have enhanced the incentive for the domestic firms to export. This is clearly a positive sign, and reveals an improvement in the competitiveness of the domestic firms.
Technology Imports: Technology Imports is one of the important determinants of the productivity growth of the firms. Firms usually import technology as a means to upgrade their existing technology. In addition, the imported technology may enable the firms to obtain monopolistic rents by using the foreign technology previously not available in the country. Technology imports can be broadly classified as both embodied technology consisting of capital goods and disembodied technology in the form of blueprints and licence fees. We observe from the sample firms that the technology imports has declined in both the local and foreign firms. The decline in the technology imports can be explained by the fact that licensing or technology collaboration is not longer considered by firms as a favourite means to obtain foreign technology. This is especially true in the context of a liberalised regime, in which the firms have the option to start a joint venture or strategic alliances with foreign firms.
3.2 Comparison of the Total Factor Productivity between Foreign firms and Domestic Firms
We follow the model proposed by Aitken and Harrison (1999) to examine whether the foreign firms are more productive. They use an augmented production function to examine the effect of foreign ownership on firm productivity within a region or an industry. We use a log-linear production function to verify whether foreign ownership has a positive association with increased productivity.
20 lnYijt = α + β1lnKijt+ β2lnLijt+ β3lnMijt+ β4FS_Firmijt+ εijt (1)
The log of output is regressed on a vector of inputs and a share of foreign ownership. The variable FS_Firmijt is refers to the ownership variable. This variable takes the value 1 for those firms whose share of foreign capital exceed 10 per cent or zero otherwise. We expect the coefficient of FS_Firmijt to be positive and significant. Inputs consists of materials Mijt, labour Lijt measured by number of employees and capital stock Kijt. The above equation is estimated using the OLS method. We also included an annual time dummy as well as industry dummy to control for differences in time and industry effects. The estimated results are presented in the Table 5. As expected the coefficient of the variable FS_Firmijt is positive and significant. This result clearly corroborates with our
notion that those firms with foreign participation in its equity are more productive than the domestic firms.
Table 5 TFP Comparison between FDI firms and Non-FDI firms Dependent variable ln Output
FS_Firmijt 0.13*** (0.022) lnK 0.29*** (.007) lnL 0.40*** (0.008) lnM 0.30*** (0.007) Constant -0.91*** (0.022)
Industry Dummies Yes
Year Dummies Yes
R2 0.68
No. of Observations
12176
Time Period 1994-2002
21 *** Shows significance at 1% level
Empirical Model
We follow the model employed by the previous studies on spillover effects of FDI by estimating a log linear augmented Cobb-Douglas production function. The production function is augmented of foreign presence apart from the regular input variables. The basic model can be represented as follows.
lnYijt = α + β1lnKijt+ β2lnLijt+ β3lnMijt+ β4Horizontaljt+ β5Verticaljt + εijt (2) where, Yijt the output by firm i in the jth industry at the time period t. The log of value
added is regressed on a vector of inputs and a measure of foreign presence. The variable
horizontal represents the share of foreign firms output in industry j at time period t.
Vertical captures the effect of multinationals on the domestic input suppliers. Inputs consists of materials Mijt, labour Lijtmeasured by number of employees and capital stock Kijt.
The above model can be estimated using Ordinary Least Squares Method (OLS). However, the estimation based on OLS poses the problem of consistency. The estimation of above model requires the strict assumption of exogenity of the variables. But the recent debates on production function estimation suggested that the exogenity assumption is will be violated in the case of OLS estimation of production function (Griliches and Mairesse 1998). The firms respond to productivity shock by using more amounts of inputs. Therefore, both labour and material variable is endogenous (Capital is generally considered as a fixed factor). As a result, there might be a correlation between the unobserved productivity shock and the inputs. Hence, OLS estimates will be biased. Griliches and Mairesse (1998) suggest that by using a first difference form of the model specification, the bias arising from the endogenity can be controlled.
While estimating the production augmented of foreign presence, there is a need to control for the industry specific effects. It is found that foreign firms tend to invest in productive firms in the host country. Therefore, if the industry effects are not controlled for, the estimated results tend to be biased and inconsistent. Often it is found that OLS estimates tend to give positive and significant results about the spillover effects. The earlier strand
22
of work on FDI and spillover using cross-sectional data, which did not control for industry and time effects often found positive results. This positive correlation may be attributed to the fact that foreign investment is often attracted to productive industries. Thus if the industry effects are not controlled for, the positive results arising seems to be a spurious one.
We use a first difference model to eliminate the differences in productivity level across industries. First differencing procedure enables us to eliminate the time invariant firm specific productivity effects. Along with the first difference model, we also include a group of industry and time dummy to get rid of the omitted variable bias and time invariant factor. By including the dummies, we can control for the differences in industry and regional effects such as long-term strategies of the firm, infrastructure and technological opportunities (Marin and Bell 2004). Therefore the equation 2 can be written as
lnΔYijt = α + β1lnΔKijt+ β2lnΔLijt+ β3lnΔMijt+ β4ΔHorizontaljt+ β5ΔVerticaljt + αj + αt + εijt (3) where, represent Mijt, Lijt and Kijt represent material expenses, labour and capital
respectively. The variables Horizontal and Vertical are same as defined above. αj and αt
are dummy variables representing industry and time effects.
Results and Discussion
In this section we discuss about the results of the spillover effects based on different model specifications. Model 1(equation 2) was estimated using a pooled OLS method. As expected we find that the spillover variable Vertical is positive and significant (Table 6). The positive and significant result may be due to the fact that it did not control for the industry and time effects. We can observe that horizontal variable is negative and is not statistically significant.
23 Table. 6 OLS Estimation of Equation 2
Dependent Variable lnY
Constant 0.875*** (0.020) lnK 0.17*** (0.007) lnL 0.27*** (0.008) lnM 0.49*** (0.007) Horizontal (Output) -0.03 (0.063) Vertical (Output) 0.35*** (0.041) Observations 16191 R-Sq 0.72 Time Period 1994-2002
Notes: The figures in the brackets are standard errors adjusted for heteroscedasticity *** Shows significance at 1% level
In the second stage, in order to strengthen the results we estimate the first difference model. Estimation results are given below. The estimation results for the all firms and domestic firms separately are given below in the Table 7 below.
Column 1 in the table reports the results of the spillover effects for all the firms. We can observe from the table that the coefficient of the horizontal spillover variable is positive but not significant. But the vertical spillover variable loses the significance and it becomes negative. We ran the same model consisting of the domestic firms. The results are similar compared to the estimates based on all firms. The horizontal spillover variable is not statistically significant even though the coefficient is positive. The sign of the backward spillover variable is negative and insignificant.
Our results about the lack of horizontal spillover are in concordance with the recent studies finding either negative or insignificant results (Aitken and Harrison 1999; Smarynska 2004, Kathuria 2001). The lack of horizontal spillovers can be due to the fact that foreign firms can prevent the leakage of technology to its competitors in the same industry. We find the vertical spillovers are negative and not significant in both the specifications. The recent debate that spillovers occur across industries than within
24
industries cannot be validated from our results. We find that those domestic firms supplying to the multinational firms are not able to reap any productivity improvements in the upstream sectors.
Table 7 OLS Estimates of the First Difference Model All Firms Domestic Firms
Δ Horizontal 0.464 (0.302) 0.055 (0.362) Δ Vertical -0.437 (0.529) -0.585 (0.565) Δ lnK 0.196*** (0.010) 0.134*** (0.021) Δ lnL 0.299*** (0.010) 0.145*** (0.018) Δ lnM 0.464*** (0.011) 0.349*** (0..034)
Industry Dummies Yes Yes
Year Dummies Yes Yes
R2 0.734 0.732
No. of Observations
10226 8914
Notes: The figures in the brackets are standard errors adjusted for heteroscedasticity. ***, **, * Shows significance at 1%, 5% and 10% respectively
Conclusion
During the nineties, India has attempted major changes in its economic policy by adopting a liberalised industrial and trade regime. It was undertaken with a view to improve efficiency and productivity as well as to improve the competitiveness of Indian industries. The policy makers have undertaken several measures to attract foreign direct investment to the country. From the data we have observed that during the last fifteen years, the foreign direct investment inflows have increased by almost ten fold.
25
In this study we have attempted to examine the spillover effects of foreign direct investment in Indian manufacturing industries. We use a firm level data of Indian manufacturing industries during the period 1994-2002 for this purpose. We investigate both the horizontal and vertical spillover effects associated with the FDI. The results of the study indicate a positive spillover for those domestic firms supplying to foreign subsidiaries. However, the lack of significance of the horizontal spillover is in congruence with the results of the other studies carried out for India (Kathuria 2001, 2002) as well as other developing and transition economies (Aitken and Harrison 1999; Djakov and Hoekman 2000; Konings 2001; Narula and Marin 2005).
Recent studies on spillover effects of FDI have looked into the possibility of finding positive effects of veritical spillovers. Following the standard methodology, (Smarynska Javorick 2004; Blalock 2002; Schoors and Vander tool 2001), we also attempted to capture the vertical spillover effects. We find that the local suppliers are not getting benefits from the contacts with the foreign firms. The negative results indicate the possibility of lack of local sourcing by the multinationals. The evidence of negative vertical spillover can be explained by the fact the foreign firms investing in India may not be sourcing inputs from domestic suppliers. It may be due to the fact that foreign firms are unable to find local suppliers, which satisfy their quality requirements. Another possibility might be a policy of “cherry picking” (Javorick and Spatareanu 2005) by the foreign firms. It means that multinational firms source inputs only from the productive local firms. As a result, domestic firms in the upstream sector may not experience any productivity improvement.
Since, there are no previous studies, which looked in to the vertical spillover effects of FDI in Indian manufacturing; we are unable to compare our results. But a recent study on vertical spillover in Indian Pharmaceutical industry report existence of negative spillovers of FDI in the upstream sector (Thangavelu and Pattnayak 2005). But our results about the negative vertical spillover effects are similar to the recent findings of negative horizontal and vertical spillover effects of FDI with the existence of negative vertical spillover
26
effects in some of the transition economies (Yudeva et al. 2003 for Russia; Merlevede & Schoors 2005 for Romania).
References
Ahluwalia, I. J. (1991), “Productivity and Growth in Indian Manufacturing”, New Delhi: Oxford University Press.
Aitken, B. J. and A. E. Harrison (1999), “Do Domestic Firms Benefit from Direct Foreign Investment? Evidence from Venezuela”, American Economic Review, Vol. 89, pp. 605-618.
Balakrishnan, P., K. Pushpangadan and M. S. Babu (2000), “Trade Liberalisation and Productivity Growth in Manufacturing: Evidence from Firm-Level Panel Data”,
Economic and Political Weekly, October. Vol. 35, No. 41, pp. 3679-82.
Balasubramanyam, V. N. and V. Mahambare (2003), “Foreign Direct Investment in India”, Lancaster University Management School Working Paper 2003/001, University of Lancaster, U.K.
Blalock, G. (2002), “Technology Adoption from Foreign Direct Investment and Exporting: Evidence from Indonesian Manufacturing”, PhD Thesis, Haas Business School, University of California Berkley.
Blomstrom, M and A. Kokko (1998), “Multinational Corporations and Spillovers”,
Journal of Economic Surveys, Vol. 12, pp. 247-277.
Blomstrom, M and F. Sjoholm (1999), “FDI, Technology Transfer and Spillovers: Does Local Competition with Multinational Matter”, European Economic Review, Vol. 43, pp. 915-923.
Blomström, M. and E. Wolff (1994), “Multinational Corporations and Productivity Convergence in Mexico”, in W. Baumol, R. Nelson and E. Wolff (Eds.)
Convergence of Productivity: Cross-National Studies and Historical Evidence, London: Oxford University Press.
Blomstrom, M. and H. Persson (1983), “Foreign Investment and Spillover Efficiency in an Underdeveloped Economy: Evidence from the Mexican Manufacturing Industry”, World Development, Vol. 11, pp. 493-501.
Blyde, J., M. Kugler and E. Stein (2005), “Exporting vs. Local Sourcing by Multinational Subsidiaries: Which Determines Foreign Direct Investment Spillovers?, mimeo, University of Southampton.
Castellani, D and A. Zanfei (2003), “Technology Gaps, Absorptive Capacity and the Impact of Inward Investments on Productivity of European Firms”, Economics of Innovation and New Technology, Vol. 12, No. 3, pp.555-576.
Caves, R. E. (1974), “Multinational Firms, Competition, Productivity in Host-Country Markets”, Economica, Vol. 41, pp. 176-193.
Caves, R. E. (1996), Multinational Enterprises and Economic Analysis, Cambridge: Cambridge University Press, Second Edition.
Central Statistical Organisation (2005), “Input-Output Transactions Table 1998-99”, New Delhi: Ministry of Statistics and Programme Implementation.
Costa, I. and S. R. de Queiroz. (2002), “Foreign Direct Investment and Technological Capabilities in Brazilian Industries”, Research Policy, vol. 31, pp. 1431-1443.
27
Dunning, J. (1993), Multinational Enterprises and the Global Economy, Wokingham : Addison-Wesley.
Girma, S. (2005),“Absorptive Capacity and Productivity Spillovers from FDI: A Threshold Regression Analysis”, Oxford Bulletin of Economics & Statistics, Vol. 67, No. 3, pp. 281-2005.
Globerman, S. (1979), “Foreign Direct Investment and Spillover Efficiency Benefits in Canadian Manufacturing Industries”, Canadian Journal of Economics, Vol. 12, pp. 42-56.
Griliches, Z. and J. Mairesse (1998), “Production Function; Search for Identification”, in S. Strom (ed.) Econometrics and Economic Theory in the 20th Century, Cambridge: Cambridge University Press.
Haddad, M. and A. E. Harrison (1993), "Are There Positive Spillovers from Direct Foreign Investment? Evidence from Panel Data for Morocco", Journal of Development Economics, Vol.42, pp. 51-74.
Hymer, S. (1976), “The International Operations of National Firms: A Study of Foreign Direct Investment”, Cambridge, Massachusetts: MIT Press.
Javorick, B. S. (2004), “Does Foreign Direct Investment Increase the Productivity of Domestic Firms? In Search of Spillovers through Backward Linkages”, American Economic Review, Vol.94, No.3, pp.605-627.
Javorick, B. S. and M. Spatareanu (2003), “To Share or not to Share: Does Local Participation Matter for Spillovers from Foreign Direct Investment”, World Bank Policy Research Paper No.3118, Washington.
Javorick, B. S. and M. Spatareanu (2005), “Disentangling FDI Spillover Effects: What do Firm Perception Tell Us?”, in T. H. Moran, E. Graham and M. Blomstrom (eds)
Does Foreign Direct Investment Promote Development?, Washington: Institute for International Economics.
Kathuria, V. (2001), "Foreign Firms, Technology Transfer and Knowledge Spillovers to Indian Manufacturing Firms - A Stochastic Frontier Analysis", Applied Economics, Vol.33, No. 5, pp. 625-42.
Kathuria, V. (2002), “Liberalisation, FDI, and Productivity Spillovers-an Analysis of Indian Manufacturing Firms”, Oxford Economic Papers, Vol. 54, pp.688-718. Kokko, A. (1994), “Technology, Market Characteristics and Spillovers”, Journal of
Development Economics, Vol. 43, pp. 279-93.
Konings, J. (2001), “The effects of Direct Foreign Investment on Domestic Firms: Evidence from Firm Level Panel Data in Emerging Economies”, Economics of Transition, vol. 9, no. 3, pp. 619 - 633.
Kugler, M. (2001), “The Diffusion of Externalities from Foreign Direct Investment: The Sectoral Pattern of Technological Spillovers”, mimeo, University of Southampton.
Kumar, N. (1994),“Multinational Enterprises and Industrial Organisation; The Case of India”, New Delhi: Sage Publications India Pvt Ltd.
Lall, S. (1978), “Transnational, Domestic Enterprises and Industrial Structure in Host LDCs: A Survey”, Oxford Economic Papers, Vol. 30, No.2, pp.217-248.
Lall, S. (1997), “Investment, Technology and International Competitiveness” in John H. Dunning and Khalel A. Hamdani (eds) The New Globalism and Developing Countries, Tokyo: UNU Press.
28
Marin, A. and M. Bell (2004), “Technology Spillovers from Foreign Direct Investment (FDI): an Exploration of the Active Role of MNC Subsidiaries in the Case of Argentina in the 1990s”, SPRU Electronic Working Paper Series, October. Markusen, J. and A. J. Venables (1999), “Foreign Direct Investment as a Catalyst for
Industrial Development”, European Economic Review, Vol. 43, No.2, pp. 335-356.
Merlevede, B and K. Schoors (2005), “Conditional Spillovers from FDI Within and Between Sectors: Evidence from Romania”, Department of Economics and CERISE, University of Ghent, October.
Narula, R. and A. Marin (2005), “Exploring the Relationship between Direct and Indirect Spillovers from FDI in Argentina", MERIT Research Memoranda 2005-024, Maastricht Economic Research Institute on Innovation and Technology.
Schoors, K and B. Van Der Tol (2002), “Foreign Direct Investment Spillovers within and between Sectors: Evidence from Hungarian Data”, Ghent University Working Paper 02/157, Belgium.
Siddharthan, N. S. and K . Lal (2004), “Liberalisation, MNE and Productivity of Indian Enterprises”, Economic and Political Weekly, Vol. pp. 448-452.
Sjöholm, F. (1999), “Technology Gap, Competition and Spillovers from Direct Foreign Investment: Evidence from Establishment Data, Journal of Development Studies, Vol. 36, pp.53-73.
Thangavelu, S. M. and Pattnayak, S. S. (2005), “Linkages Spillovers and Foreign Ownership: Evidence from the Indian Pharmaceutical Firms”, Paper Presented at the 32nd European Association of Research in Industrial Economics (EARIE) Conference, Portugal.
UNCTAD. World Investment Report (various issues)
Yudeva, K., K. Kozlov, N. Melentieva and N. Ponomareva (2003), “Does Foreign Ownership Matter? Russian Experience”, Economics of Transition, Vol. 11, No.3, pp. 383-410.
Zukowska-Gagglemann, K. (2000), “Productivity Spillovers from Foreign Direct Investment in Poland”, Economic Systems, Vol. 24, No. 3, pp.223-56.
29
Appendix I
Construction of Variables Output
PROWESS data contains information on value of total output total by each firm belonging to particular industry group. This was deflated using industry specific wholesale price index. The wholesale price index is obtained from the “Index of Wholesale Prices in India with base year as 1994=100”, provided by www.circonindia.com.
Capital
The difficult task faced by the researcher while estimating total factor productivity is the correct measurement of the capital stock variable. For this purpose we closely follow the methodology provided by Srivastava (1996) and Balakrishnan et al (2000). They use Perpetual Inventory Method, which correct for the fact that capital involve historical cost. Therefore, the straightforward application of the perpetual inventory method is not possible. The capital stock has to be converted into an asset value at replacement cost. For this purpose, we measure the capital stock at its replacement cost for the base year (we assume to be 1994-95). We follow Balakrishnan et al (2000) to arrive at a revaluation factor. The revaluation factor is constructed assuming that life of the machinery and equipment is 20 years and the growth of the investment is constant throughout this period. We also assume constant rate of change for the prices of the capital stock. The revaluation factor obtained is used to convert the capital in the base year into capital at the replacement cost at current prices. We then deflate these values to arrive at the values of capital stock in constant prices for the base year. The deflator used for the purpose in constructed from the series on gross capital formation. Subsequent years’ capital stock is arrived by using the sum of investment using the perpetual inventory method.
Labour
The PROWESS database provides information on wages and salaries. No information on the number of employees is available. Therefore, we need to use this information to arrive at the mandays of work for each firm. Mandays at the firm level is arrived by
30
dividing the salaries and wages at the firm level by the average wage rate of the industry to which each firm belongs. It is arrived using the following formula
Number of mandays per firm = Salaries and Wages/Average Wage Rate
In order to arrive at the average wage rate, we make use of the Annual Survey of Industries (ASI) data. ASI contains information on Total Emoluments as well as Total Mandays for relevant industry groups. At the time of this study, ASI data was available only till 2001, and we have extrapolated the values for the year 2002. We obtain average wage rate by diving total emoluments by total mandays. It can be represented by:
Average Wage Rate = Total Emoluments/Total Mandays Materials
We follow Balakrishnan et al. (2000) methodology to construct the materials variable. The materials bill was inflated by a material input-output price index. The input-output coefficients for the year 1997 have been used as the weights to combine the wholesale prices of relevant materials. The input-output weights were obtained from the CSO’s input-output table for 1997-1998 and the relevant whole sale price index is obtained from the “Index of Wholesale Prices in India with base year as 1994=100”, provided by www.circonindia.com.
Appendix II
The latest Input-Output table available for India pertains to the year 1998-99. The input-output table is provided by the Central Statistical Organisation (http://mospi.nic.in). The input-output table consists of two matrices: absorption matrix (commodity x industry) and makemat (industry x commodity). For the purpose of our study, we need to create an
industry x industry matrix. The procedure for constructing an industry x industry matrix is explained in detail below.
The absorption matrix consists of values of commodities supplied to different industries for final use as well as intermediate inputs. The make matrix represent the values of output produced by different industries. As mentioned above our purpose is to construct an industry x industry matrix. Therefore as a first step, we need to aggregate the
input-31
output table for the manufacturing sector to two-digit level. Secondly, a matrix of coefficient (we call it matrix X) has been created by dividing each row of the absorption matrix by the total output of the commodity. We create another matrix Y (using the make matrix) by dividing the each row by the total output produced by the respective industry. As a final step, we create a new matrix Z=YX. The new matrix Z is nothing but an
industry x industry matrix. Each row of the matrix Z represents the total industry output delivered to different industries in the economy.
32 I-O Sector Classification
Industry Classification IOTT Sector No.
Food Products and Beverages 33-39
Tobacco Products 40
Textiles 41-46
Wearing Apparel; Dressing and Dyeing of Fur 47-49
Tanning and Dressing of Leather; Manufacture of Luggage, Handbags Saddlery, Harness and Footwear
54-55 Wood and of Products of Wood and Cork, Except
Furniture; Manufacture of Articles of Straw and Plating Materials
51
Paper and Paper Products 52
Publishing, Printing and Reproduction of Recorded Media 53
Coke, Refined Petroleum Products and Nuclear Fuel 58-59
Chemicals and Chemical, Products 60-68
Rubber and Plastic Products 56-57
Other Non-Metallic Mineral Products 69-71
Basic Metals 72-75
Fabricated Metal Products, Except Machinery and
Equipments 76-77
Machinery and Equipment N.E.C. 78,79,80,81,83
Office, Accounting and Computing Machinery 82
Electrical Machinery and Apparatus N.E.C. 84-87,89
Manufacture of Radio, Television and Communication Equipment and Apparatus
88,90 Medical, Precision and Optical Instruments, Watches and
Clocks
97
Motor Vehicles Travelers and Semi-Trailers 93-95
Other Transport Equipment 91,92,96
34 THE UNU-MERIT WORKING PAPER SERIES
# 2006-001 A Knowledge Economy Paradigm and its Consequences by Luc Soete. # 2006-002 Public-Private Sector Partnerships in an Agricultural System of Innovation:
Concepts and Challenges by Andy Hall.
# 2006-003 Capacity Development for Agricultural Biotechnology in Developing Countries: Concepts, Contexts, Case Studies and Operational Challenges of a Systems Perspective by Andy Hall and Jeroen Dijkman.
# 2006-004 Technological Capabilities with Different Degree of Coherence: A Comparative Study of Domestic-Oriented vs. Export-Driven Bulgarian Software Companies by Rossitza Rousseva.
# 2006-005 Small Islands, New Technologies and Globalization: A Case of ICT adoption by SMEs in Mauritius by Kaushalesh Lal and Aveeraj Sharma Peedoly.
# 2006-006 Beyond Unobserved Heterogeneity in Computer Wage Premiums; and Data on Computer use in Germany, 1997-2001. Double paper by Joan Muysken, Sybrand Schim van der Loeff and Valeria Cheshko.
# 2006-007 Learning in Local Systems and Global Links: The Otigba Computer Hardware Cluster in Nigeria by Banji Oyelaran-Oyeyinka
# 2006-008 Breaking the Fence: Patent Rights and Biomedical Innovation in “Technology Followers” by Padmashree Gehl Sampath
# 2006-009 Taxation and Technology Adoption: A Hotelling Approach by Ben Kriechel and Thomas Ziesemer
# 2006-010 Foreign Direct Investment and Technology Spillovers: Evidence from the Indian Manufacturing Sector by Subash Sasidharan
